方位(导航)
振动
感应电动机
加速度计
结构工程
状态监测
计算机科学
断层(地质)
滚柱轴承
工程类
声学
机械工程
地质学
物理
人工智能
电压
地震学
电气工程
操作系统
润滑
作者
Dileep Kumar,Sanaullah Mehran,Muhammad Zakir Shaikh,Majid Hussain,Bhawani Shankar Chowdhry,Tanweer Hussain
出处
期刊:Data in Brief
[Elsevier]
日期:2022-05-23
卷期号:42: 108315-108315
被引量:13
标识
DOI:10.1016/j.dib.2022.108315
摘要
Rotating machines as core component of an industry can effectively be monitored through vibration analysis. Considering the importance of vibration in industrial condition monitoring, this article reports and discusses triaxial vibration data for motor bearing faults detection and identification. The data is acquired using a MEMS based triaxial accelerometer and the National Instruments myRIO board. The bearing conditions include healthy bearing, bearings with inner race faults, and bearings with outer race faults. For each faulty bearing condition, the three-phase induction motor is operated under three different load conditions. The dataset can be used to assess performance of newly developed methods for effective bearing fault diagnosis. Mendeley Data. http://dx.doi.org/10.17632/fm6xzxnf36.2.
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